AIMC Topic: Aged

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Construction of an artificially intelligent model for accurate detection of HCC by integrating clinical, radiological, and peripheral immunological features.

International journal of surgery (London, England)
BACKGROUND: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. We aimed to develop a model with multimodal features (MMF) using artificial intelligence (AI) approaches to enhance the p...

Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.

Clinical and translational gastroenterology
INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool using mathematical algorithms to predict severity and manage fluid resuscitation needs based on the physiologic parameters of individual patients. Our a...

Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study.

Frontiers in endocrinology
BACKGROUND: While the Cardiometabolic Index (CMI) serves as a novel marker for assessing adipose tissue distribution and metabolic function, its prognostic utility for cardiovascular disease (CVD) events remains incompletely understood. This investig...

Barriers and enablers for the deployment of large language model-based conversational robots for older adults: A protocol for a systematic review of qualitative studies.

PloS one
BACKGROUND: Artificial intelligence-powered conversational agents have immense potential to provide social companionship and support for older adults. However, the deployment of large language model (LLM)-based conversational robots for seniors faces...

Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach.

PloS one
BACKGROUND: Non-small-cell lung cancer (NSCLC) and its surgery significantly increase the venous thromboembolism (VTE) risk. This study explored the VTE risk factors and established a machine-learning model to predict a failure of postoperative throm...

AI-Quantitative CT Coronary Plaque Features Associate With a Higher Relative Risk in Women: CONFIRM2 Registry.

Circulation. Cardiovascular imaging
BACKGROUND: Coronary plaque features are imaging biomarkers of cardiovascular risk, but less is known about sex-specific patterns in their prognostic value. This study aimed to define sex differences in the coronary atherosclerotic phenotypes assesse...

Impact of harmonization on predicting complications in head and neck cancer after radiotherapy using MRI radiomics and machine learning techniques.

Medical physics
BACKGROUND: Variations in medical images specific to individual scanners restrict the use of radiomics in both clinical practice and research. To create reproducible and generalizable radiomics-based models for outcome prediction and assessment, data...

Structural and metabolic topological alterations associated with butylphthalide treatment in mild cognitive impairment: Data from a randomized, double-blind, placebo-controlled trial.

Psychiatry and clinical neurosciences
AIMS: Effective intervention for mild cognitive impairment (MCI) is key for preventing dementia. As a neuroprotective agent, butylphthalide has the potential to treat MCI due to Alzheimer disease (AD). However, the pharmacological mechanism of butylp...

Immune profile and routine laboratory indicator-based machine learning for prediction of lung cancer.

Computers in biology and medicine
INTRODUCTION: Early diagnosis of lung cancer is still a challenge by using current diagnostic methods.

Automated generation of echocardiography reports using artificial intelligence: a novel approach to streamlining cardiovascular diagnostics.

The international journal of cardiovascular imaging
Accurate interpretation of echocardiography measurements is essential for diagnosing cardiovascular diseases and guiding clinical management. The emergence of large language models (LLMs) like ChatGPT presents a novel opportunity to automate the gene...